The present invention relates to image processing, and more particularly relates to image processing systems for the inspection of items decorated with a multicolored pattern.
Several systems have been proposed to determine quality of a color decoration of an item. Some of these systems use an electronic image processor to evaluate coloration as part of an assembly line process. Typically, these systems employ an array of optical sensors to generate a pixelated image of the item for analysis by the processor. One problem with this approach is that the decoration is usually randomly oriented with respect to the optical sensors, making electronic image evaluation difficult.
One attempt to overcome this problem is to transform the physical space image of the object undergoing inspection into a color space representation. This color space representation is typically independent of physical space orientation of the object. U.S. Pat. Nos. 5,120,126 to Wertz et al., 5,374,988 to Wertz et al., and 5,339,963 to Tao are cited as sources of general information concerning color space applications to inspection and sorting systems.
FIG. 1A provides a perspective view of color space defined in terms of Red, Green, Blue (RGB) coordinates. This form of color space is convenient for characterizing colors of images supplied by the RGB output of many types of cameras. Another color space representation is presented in FIG. 1B in terms of the Hue, Saturation, Intensity (HSI) color space coordinates. Methods to convert between RGB and HSI color space image representations are well known. The "Line of Grays" common to both FIGS. 1A and 1B indicates the nature of this conversion. Notably, color space could also be defined in terms of the Yellow, Cyan, Magenta (YCM) color space coordinate triad or some other triad of coordinates as would occur to one skilled in the art. Furthermore, a two dimensional color space may be defined in terms of two independent coordinates of a three coordinate system.
One type of color image evaluation process, which typically utilizes color space transformations, partitions a color image into uniformly colored regions using a process commonly called "segmentation." The resulting "segmented image" looks like a stained glass portrayal or a comic strip cartoon of the item. The uniform color regions are generally determined by correlating each color of the actual image to the closest color in a set of reference colors. There are usually significantly fewer colors in the reference color set than are initially presented in the actual image. Segmentation typically eliminates gradual color changes, reflection differences, and other minor variations that may hamper image processing. Furthermore, segmentation generally simplifies the evaluation process by reducing the part image to a pre-defined number of known reference colors. For segmentation systems where the actual image is provided in a pixelated format, each region is typically correlated by addressing a segmentation look-up table with each pixel color value. These systems output a common reference color for a selected range of pixel color values to provide a corresponding segmented image. U.S. Pat. Nos. 4,414,635 to Gast et al. and 5,335,293 to Vannelli et al. are cited generally as sources of additional information concerning segmentation.
Although typically free from the random orientation problem, color space inspection systems frequently suffer from being unable to cost effectively indicate the nature of a detected variation in a multicolor pattern for subsequent confirmation by an operator. Also, the detection of pattern variations, deviations, or defects often requires complex processing equipment and a significant amount of processing time. Unfortunately, these systems may even become the principle limiting factor for the speed of an assembly line. Thus, a need remains for faster and more reliable evaluation of color decorations on items moving on a conveyor.